Zvi Hochman

An overview of APSIM, a model designed for farming systems simulation

The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIMs structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided.

Re-inventing model-based decision support with Australian dryland farmers. 4. Yield Prophet® helps farmers monitor and manage crops in a variable climate.

In Australia, a land subject to high annual variation in grain yields, farmers find it challenging to adjust crop production inputs to yield prospects. Scientists have responded to this problem by developing Decision Support Systems, yet the scientists’ enthusiasm for developing these tools has not been reciprocated by farm managers or their advisers, who mostly continue to avoid their use. Preceding papers in this series described the FARMSCAPE intervention: a new paradigm for decision support that had significant effects on farmers and their advisers. These effects were achieved in large measure because of the intensive effort which scientists invested in engaging with their clients. However, such intensive effort is time consuming and economically unsustainable and there remained a need for a more cost-effective tool. In this paper, we report on the evolution, structure, and performance of Yield Prophet®: an internet service designed to move on from the FARMSCAPE model to a less intensive, yet high quality, service to reduce farmer uncertainty about yield prospects and the potential effects of alternative management practices on crop production and income. Compared with conventional Decision Support Systems, Yield Prophet offers flexibility in problem definition and allows farmers to more realistically specify the problems in their fields. Yield Prophet also uniquely provides a means for virtual monitoring of the progress of a crop throughout the season. This is particularly important for in-season decision support and for frequent reviewing, in real time, of the consequences of past decisions and past events on likely future outcomes. The Yield Prophet approach to decision support is consistent with two important, but often ignored, lessons from decision science: that managers make their decisions by satisficing rather than optimising and that managers’ fluid approach to decision making requires ongoing monitoring of the consequences of past decisions.

Potential to improve on-farm wheat yield and WUE in Australia

Water-use efficiency (WUE) is defined here as the ratio of grain yield (kg/ha) to crop water use by evapotranspiration (mm). Much of the WUE literature has focussed on either the determination of the boundary of attainable WUE for any amount of available water, or on the practicalities of measurement of the WUE of a crop. While these are important issues for defining the gap between the attained and the potential WUE, little progress has been reported on clarifying the components that contribute to this gap or on how it can be bridged. To address these questions, we analysed 334 wheat fields for which we had the data necessary to both calculate WUE and to simulate crop growth and water use. Simulations were conducted through Yield Prophet®, an on-line version of the APSIM systems model. For this dataset, evapotranspiration accounted for 69% of observed yield variation, although the more commonly used growing-season (April–October) rainfall accounted for 50%. Considering that evapotranspiration efficiency does not account for a wide range of potentially yield-limiting factors including soil and fertiliser nitrogen supply, crop phenology, and sowing dates, or rainfall distribution, these results reinforce the importance of evapotranspiration efficiency as a yield determinant for well managed crops in water-limited environments. WUE attained over the whole dataset was 15.2 kg grain/ha.mm (x-intercept = 67 mm), although this value contained data subsets with important differences in WUE based on soil water-holding capacity and regional diversity. Yield Prophet® simulated commercial wheat yields with RMSDs of 0.80 t/ha (r2 = 0.71), with some systematic error between observed and simulated yields. Simulated crops achieved a higher WUE (16.9 kg grain/ha.mm; x-intercept = 72 mm) than the observed crops, probably because APSIM does not account for effects of factors such as weeds, pests and diseases and impacts of severe weather. Simulated ‘what-if’ analysis suggested that further improvement in WUE may be achieved with an early sowing strategy or a higher nitrogen input strategy. A ‘yield maximising’ strategy that included an optimal plant density, early sowing date, and higher nitrogen inputs resulted in an average WUE (21.4 kg grain/ha.mm; x-intercept = 80 mm) that is close to the previously reported (French-Schultz) boundary of WUE. This outcome suggests a great deal of scope for Australian wheat growers to adopt strategies that improve their WUE. Yield Prophet® farmers have already demonstrated significant improvement in on-farm WUE compared with previous studies. However, additional improvements will only be partially realised due to considerations of the cost: benefit ratio and risk in a highly variable climate, and the operational feasibility of these strategies with current technologies.

Re-inventing model-based decision support with Australian dryland farmers. 3. Relevance of APSIM to commercial crops

Crop simulation models relevant to real-world agriculture have been a rationale for model development over many years. However, as crop models are generally developed and tested against experimental data and with large systematic gaps often reported between experimental and farmer yields, the relevance of simulated yields to the commercial yields of field crops may be questioned. This is the third paper in a series which describes a substantial effort to deliver model-based decision support to Australian farmers. First, the performance of the cropping systems simulator, APSIM, in simulating commercial crop yields is reported across a range of field crops and agricultural regions. Second, how APSIM is used in gaining farmer credibility for their planning and decision making is described using actual case studies. Information was collated on APSIM performance in simulating the yields of over 700 commercial crops of barley, canola, chickpea, cotton, maize, mungbean, sorghum, sugarcane, and wheat monitored over the period 1992 to 2007 in all cropping regions of Australia. This evidence indicated that APSIM can predict the performance of commercial crops at a level close to that reported for its performance against experimental yields. Importantly, an essential requirement for simulating commercial yields across the Australian dryland cropping regions is to accurately describe the resources available to the crop being simulated, particularly soil water and nitrogen. Five case studies of using APSIM with farmers are described in order to demonstrate how model credibility was gained in the context of each circumstance. The proposed process for creating mutual understanding and credibility involved dealing with immediate questions of the involved farmers, contextualising the simulations to the specific situation in question, providing simulation outputs in an iterative process, and together reviewing the ensuing seasonal results against provided simulations. This paper is distinct from many other reports testing the performance and utility of cropping systems models. Here, the measured yields are from commercial crops not experimental plots and the described applications were from real-life situations identified by farmers. A key conclusion, from 17 years of effort, is the proven ability of APSIM to simulate yields from commercial crops provided soil properties are well characterised. Thus, the ambition of models being relevant to real-world agriculture is indeed attainable, at least in situations where biotic stresses are manageable.

Scope for improved eco-efficiency varies among diverse cropping systems

Global food security requires eco-efficient agriculture to produce the required food and fiber products concomitant with ecologically efficient use of resources. This eco-efficiency concept is used to diagnose the state of agricultural production in China (irrigated wheat–maize double-cropping systems), Zimbabwe (rainfed maize systems), and Australia (rainfed wheat systems). More than 3,000 surveyed crop yields in these three countries were compared against simulated grain yields at farmer-specified levels of nitrogen (N) input. Many Australian commercial wheat farmers are both close to existing production frontiers and gain little prospective return from increasing their N input. Significant losses of N from their systems, either as nitrous oxide emissions or as nitrate leached from the soil profile, are infrequent and at low intensities relative to their level of grain production. These Australian farmers operate close to eco-efficient frontiers in regard to N, and so innovations in technologies and practices are essential to increasing their production without added economic or environmental risks. In contrast, many Chinese farmers can reduce N input without sacrificing production through more efficient use of their fertilizer input. In fact, there are real prospects for the double-cropping systems on the North China Plain to achieve both production increases and reduced environmental risks. Zimbabwean farmers have the opportunity for significant production increases by both improving their technical efficiency and increasing their level of input; however, doing so will require improved management expertise and greater access to institutional support for addressing the higher risks. This paper shows that pathways for achieving improved eco-efficiency will differ among diverse cropping systems.

Effect of water stress with phasic development on yield of wheat grown in a semi-arid environment

Abstract Irrigated wheat crops were subjected to severe soil moisture deficits at three ontogenetic stages in a field experiment in the Negev desert, Israel. Quantitative relationships were obtained for leaf water potential as a function of relative available soil moisture in the zone of root penetration and potential transpiration and for leaf diffusive resistance as a function of leaf water potential. Stress from tillering to anthesis reduced leaf area index and grain number. Grain yield was 28% lower than the unstressed treatment in which grain yield was 779 g m−2. Stress from booting to grainfilling resulted in reduced grain number and 1000 grain weight. Grain yield was reduced by 36%. Stress during grainfilling reduced the 1000 grain weight and grain yield was 16% below the well watered control. Harvest index was unaffected by any of the stress treatments. Water use efficiency was reduced by stress and was lowest for stress between booting and grainfilling. The results of this experiment emphasize the dynamic response of a wheat crop to its water status. Especially significant in a semi-arid environment is the increased sensitivity of leaf water potential to soil moisture deficit during the linear phase of grainfilling. This undesirable response may be remedied by selection for varieties which are less sensitive to soil moisture deficit at grainfilling.

Contributions of soil and crop factors to plant available soil water capacity of annual crops on Black and Grey Vertosols

Improved methods for field measurements of plant available soil water capacity (PAWC) of Black and Grey Vertosols in Australia’s north-eastern grain region were employed to characterise 83 soil–crop combinations over 7 depth intervals to 180 cm. Soil sub-order was shown to influence all components of PAWC (means of 224 and 182 mm in Black and Grey Vertosols, respectively) with drained upper limit (DUL), bulk density (BD), and crop lower limits (CLL) showing clear separation between soil sub-orders and a trend with soil depth. In addition to soil sub-order and soil depth effects, CLL showed crop effects such that expected PAWC of various crops when adjusted for soil sub-orders were: cotton 240 mm; wheat 233 mm; sorghum 225 mm; fababean 209 mm; chickpea 197 mm; barley 191 mm; and mungbean 130 mm. A total of 549 measured CLL values were used to develop a predictive model for estimating CLL from the soil sub-order, depth, DUL, and crop by predicting a CLL as a function of DUL and a depth-dependent variable for each crop–soil sub-order. The model CLL = DUL * (a + b * DUL) explained 85% of observed variation in the measured data with no significant bias between observed and predicted data. While properly measured data would be more reliable than estimated data, where specific site accuracy is less critical, this model may be used to estimate PAWC with an acceptable degree of accuracy.

Diagnosis, extent, impacts, and management of subsoil constraints in the northern grains cropping region of Australia

Productivity of grain crops grown under dryland conditions in north-eastern Australia depends on efficient use of rainfall and available soil moisture accumulated in the period preceding sowing. However, adverse subsoil conditions including high salinity, sodicity, nutrient imbalances, acidity, alkalinity, and high concentrations of chloride (Cl) and sodium (Na) in many soils of the region restrict ability of crop roots to access this stored water and nutrients. Planning for sustainable cropping systems requires identification of the most limiting constraint and understanding its interaction with other biophysical factors. We found that the primary effect of complex and variable combinations of subsoil constraints was to increase the crop lower limit (CLL), thereby reducing plant available water. Among chemical subsoil constraints, subsoil Cl concentration was a more effective indicator of reduced water extraction and reduced grain yields than either salinity or sodicity (ESP). Yield penalty due to high subsoil Cl was seasonally variable, with more in-crop rainfall (ICR) resulting in less negative impact. A conceptual model to determine realistic yield potential in the presence of subsoil Cl was developed from a significant positive linear relationship between CLL and subsoil Cl: Since grid sampling of soil to identify distribution of subsoil Cl, both spatially across landscape and within soil profile, is time-consuming and expensive, we found that electromagnetic induction, coupled with yield mapping and remote sensing of vegetation offers potential to rapidly identify possible subsoil Cl at paddock or farm scale. Plant species and cultivars were evaluated for their adaptations to subsoil Cl. Among winter crops, barley and triticale, followed by bread wheat, were more tolerant of high subsoil Cl concentrations than durum wheat. Chickpea and field pea showed a large decrease in yield with increasing subsoil Cl concentrations and were most sensitive of the crops tested. Cultivars of different winter crops showed minor differences in sensitivity to increasing subsoil Cl concentrations. Water extraction potential of oilseed crops was less affected than cereals with increasing levels of subsoil Cl concentrations. Among summer crops, water extraction potential of millet, mungbean, and sesame appears to be more sensitive to subsoil Cl than that of sorghum and maize; however, the differences were significant only to 0.7 m. Among pasture legumes, lucerne was more tolerant to high subsoil Cl concentrations than the others studied. Surface applied gypsum significantly improved wheat grain yield on soils with ESP >6 in surface soil (0–0.10 m). Subsurface applied gypsum at 0.20–0.30 m depth did not affect grain yield in the first year of application; however, there was a significant increase in grain yield in following years. Better subsoil P and Zn partially alleviated negative impact of high subsoil Cl. Potential savings from improved N fertilisation decisions for paddocks with high subsoil Cl are estimated at ~

Using Seasonal Climate Forecasts to Manage Dryland Crops in Northern Australia — Experiences from the 1997/98 Seasons

AU10 million per annum.

Yield gap analysis of rainfed wheat demonstrates local to global relevance

In Australia, like in many other parts of the world, a significant proportion of rainfall variability is associated with the El Nino / Southern Oscillation phenomenon (ENSO). Significant, physically based lag-relationships exist between an index of the ocean/atmosphere ENSO phenomenon and future rainfall amount and temporal distribution in eastern Australia and many other areas across the globe. A skilful seasonal climate forecast provides an opportunity for farm managers to better tailor crop management decisions to the season. This forms the basis for a probabilistic crop production forecasting system used operationally in Australia where high rainfall variability is the major source of dryland yield fluctuations.